Wednesday, December 19, 2012

The TWIN Recommender System / part 2

In a previous post, more than a year ago, I had written about the TWIN (Tell Me What I Need) Personality Based Recommender System.

The paper "Evaluating the Similarity Estimator Component of the TWIN Personality-basedRecommender System" explains how that recommender performs. "In addition to the classical collaborative filtering and content based approaches, taking into account ratings, preferences and demographic characteristics of the users, a new type of Recommender System, based on personality parameters, has been emerging recently. In this paper we describe the TWIN (Tell Me What I Need) Personality Based Recommender System, and report on our experiments and experiences of utilizing techniques which allow the extraction of the personality type from text (following the Big Five model popular in the psychological research). We estimate the possibility of constructing the personality-based Recommender System that does not require users to fill in personality questionnaires."

Unfortunately, like the PersonalityML, the TWIN approach is the WRONG approach to innovate in the Personality Based Recommender Systems Arena.

Again: theBig5 personality test isgood for orientative
purposes but not good enough for predictive purposes.

Personality Based Recommender Systems are the next generation of recommender systems because they perform FAR better than Behavioural ones (past actions and pattern of personal preferences)That is the only way to improve recommender systems, to include the personality traits of their users. Have you seen they need to calculate personality similarity between users?Have you seen there are different formulas to calculate similarity?In
case you did not notice, recommender systems are morphing to ..........
compatibility matching engines, as the same used in the Online Dating Industry since years, with low success rates!!! but ...... they mostly use the Big5 to assess personality and the Pearson correlation coefficient to calculate similarity.

The RIGHT approach to innovate in the Personality Based Recommender Systems Arena is exactly the same approach to innovate in the Online Dating Industry. The 16PF5 test or similar to assess personality traits and a new method
to calculate similarity between quantized patterns.